Distribution of Variables

Suicide Rates

One of the mental health variables we want to focus on for this project is suicide rates. With this measure of mental health we can then analyze how it compares to the access to health care such as the number of mental hospitals the area or region has. This data comes from a Mental Health and Suicide Rates Kaggle Data Set where the age standardized suicide rates have been calculated for the year 2016 noting sex and country.

Sex Max Rate Min Rate Mean Rate
Both sexes 30.2 0.5 9.287156
Female 18.7 0.8 4.775229
Male 47.5 0.0 14.137615

This table indicates the means of age standardized suicide rates in 2016 for females, males, and the combination of the two. We can note that the male rates are significantly higher than the females. It also describes the ranges of values that females, males, and both sexes of the age standardized suicide rates. Males have both one of the highest rates and lowest rates.

The data that is shown in this boxplot is the average suicide rate of each contry. This boxplot shows the lowest suicide rate (Antigua and Barbuda) of 0.4666667 and the highest rate (Guyana) of 30.3333333. However, to note, the highest suicide rate is actually considered an outlier on the boxplot. The actual maximum represented here is Côte d’Ivoire with a the average suicide rate of 22.6666667.

Relationships Between Variables

How does socioeconomic status level impact prevalence of depression?

One of our objectives for this project is to better understand the correlation between mental health and socioeconomic status. This bar chart is a example of what we can analyze and examine from the Adult Depression (LGHC Indicator) dataset. In this dataset, the California Behavioral Risk Factor Surveillance Survey (BRFSS) asked California residents the question: “Has a doctor, nurse or other health professional EVER told you that you have a depressive disorder (including depression, major depression, dysthymia, or minor depression)?” This plot compares 2018 resident income and the Weighted Frequency, which refers to Frequency with the weight applied (the estimated count in the population with the combination of values).

In 2018. California residents in the lower socioeconomic class with less than a $20,000 salary have the highest weighted frequency of adult depression with 1,040,602. In contrast, California residents in the higher socioeconomic class with more than a $100,000 salary have the lowest weighted frequency of adult depression with 556,246.

How does the rate of a mental hospital affect suicidal rates?

To see if there is a correlation between suicide rates and the number of health facilities in countries, we merged the age-standardized suicide rates in 2016 with the health facilities in each country. Since GDP is an indicator of a nation’s standard of living, we were able to understand how a country’s economy reflects suicide rates and mental health facilities in countries.

Based on the visualization, most countries are heavily populated on the lower left side, indicating that most countries have low suicidal rates with low mental hospital facilities rates. However, few countries like Guyana and Lithuania have very few mental hospitals with high suicidal rates. According to the International Monetary Fund, some of the countries that have led to economic growth in 2022 are the United States, Japan, and India. The United States and India seem to have higher suicide rates with low mental health facilities. On the other hand, Japan has the highest mental hospital rate of all nations, with relatively high suicidal rates.